The automated alignment of image features from images of deformable surfaces taken at different times is difficult because over time, a deformable surface may stretch and change shape, and in so doing, the relative positions of various surface features may change. In considering human skin as such a deformable surface, registration of images can be even more difficult due to weight gain or loss, scarring, tattoo addition or removal, and hair growth or loss; additionally, photographic features may change from image to image including such things as differences in lighting, pose and angle of the photographing.
Registration of human skin images is important for detecting skin cancer because it would automate key portions of the photographic comparison process that can take highly trained dermatologists too much time to do thoroughly. Currently, skin cancer screening is performed by combining visual observations with manual handwritten tracking methods done locally in a physician's office. Digital photography has been used by some dermatologists and patients to help identify skin changes, but it remains difficult and time-consuming to compare baseline images to lesions observed at the time of a skin examination. One means of early stage skin cancer detection is to note changes over time in the appearance of moles with respect to size and coloration. The inherent difficulties in an automated approach to imaging the human body over time, aligning features of the images, and comparing those images in a reliable and clinically useful way have not yet been overcome in any known commercial implementation.
Thus, there are needs for generalized automated image registration systems and methods for registering images of deformable surfaces in particular. There are also needs for systems and methods for precisely aligning skin features in images captured over time suitable for use in skin cancer detection.